lacuna nodes need to be marked as such on read

[scpubgit/stemmatology.git] / TreeOfTexts / lib / TreeOfTexts / Model / Analysis.pm

package TreeOfTexts::Model::Analysis;

use strict;
use warnings;
use Exporter 'import';
use Text::Tradition;
use Text::Tradition::Stemma;

use vars qw/ @EXPORT_OK /;
@EXPORT_OK = qw/ run_analysis /;

my $tradition; # Global for convenience, ew.
# Returns 
sub run_analysis {
	my( $file, $stemmadot ) = @_;
	# What we will return
	my $svg;
	my $variants = [];
	
	# Read in the file and stemma
	my @lines;
	open( INFILE, "$file" ) or die "Could not read $file";
	binmode INFILE, ':utf8';
	@lines = <INFILE>;
	close INFILE;
	
	$tradition = Text::Tradition->new( 
		'Self' => join( '', @lines ),
		'linear' => 1,
		);
	my $stemma = Text::Tradition::Stemma->new(
		'collation' => $tradition->collation,
		'dot' => $stemmadot,
		);
	# We will return the stemma picture
	$svg = $stemma->as_svg;
	
	# We have the collation, so get the alignment table with witnesses in rows.
	# Also return the reading objects in the table, rather than just the words.
	
	my $all_wits_table = $tradition->collation->make_alignment_table( 'refs' );
	
	# For each column in the alignment table, we want to see if the existing
	# groupings of witnesses match our stemma hypothesis. We also want, at the
	# end, to produce an HTML table with all the variants.
	my $html_columns = 0;
	my $html_data = [];
	my $total = 0; # Keep track of the total number of variant locations
	
	# Strip the list of sigla and save it for correlation to the readings.
	my $col_wits = shift @$all_wits_table;
	
	# We will return a data structure, an array for each row that looks like:
	# { id = X, genealogical = Y, readings = [ text = X, group = Y], empty = N }
	foreach my $i ( 0 .. $#$all_wits_table ) {
		# For each column in the table, group the readings by witness.
		my $rdg_wits = {};
		my $col_rdgs = shift @$all_wits_table;
		my $rank;
		foreach my $j ( 0 .. $#{$col_rdgs} ) {
			my $rdg = $col_rdgs->[$j];
			$rank = $rdg->rank if $rdg && !$rank;  # Make a note of our rank
			my $rdg_text = '(omitted)';  # Initialize in case of empty reading
			if( $rdg ) {
				$rdg_text = $rdg->is_lacuna ? undef : $rdg->text; # Don't count lacunae
			}
			if( defined $rdg_text ) {
				# Initialize the witness array if we haven't got one yet
				$rdg_wits->{$rdg_text} = [] unless $rdg_wits->{$rdg_text};
				# Add the relevant witness, subject to a.c. logic
				add_variant_wit( $rdg_wits->{$rdg_text}, $col_wits->[$j] );
			}
		}
		
		# See if this column has any potentially genealogical variants.
		# If not, skip to the next.
		$total++ unless scalar keys %$rdg_wits == 1;
		my( $groups, $readings ) = useful_variant( $rdg_wits );
		next unless $groups && $readings;  
		
		# Initialize the data structure for the row that we will return
		my $variant_row = {'id' => $rank, 'readings' => [] };
		# Keep track of our widest row
		$html_columns = scalar @$groups if scalar @$groups > $html_columns;
		
		# We can already look up witnesses for a reading; we also want to look
		# up readings for a given witness.
		my $group_readings = {};
		foreach my $x ( 0 .. $#$groups ) {
			$group_readings->{wit_stringify( $groups->[$x] )} = $readings->[$x];
		}
		
		# For all the groups with more than one member, collect the list of all
		# contiguous vertices needed to connect them.
		# TODO: deal with a.c. reading logic
		my $sc = analyze_variant_location( $group_readings, $groups, $stemma->apsp );
		$variant_row->{'genealogical'} = keys %$sc ? 1 : undef;
		foreach my $grp ( sort keys %$group_readings ) {
			my $rdg = $group_readings->{$grp};
			push( @{$variant_row->{'readings'}}, { 'text' => $rdg, 'group' => $grp } );
		}
		
		# Now run the same analysis given the calculated distance tree(s).
# 		foreach my $tree ( 0 .. $#{$stemma->distance_trees} ) {
# 			my $dc = analyze_variant_location( $group_readings, $groups,    
# 											   $stemma->distance_apsps->[$tree] );
# 			foreach my $rdg ( keys %$dc ) {
# 				my $var = $dc->{$rdg};
# 			}
# 		}
	
		# Record that we used this variant in an analysis
		push( @$variants, $variant_row );
	}
	
	# Go through our variant rows and add the number of empty columns we need.
	foreach my $row ( @$variants ) {
		my $empty = $html_columns - scalar @{$row->{'readings'}};
		$row->{'empty'} = $empty;
	}
	
	return( $svg, $variants );
}

sub analyze_variant_location {
    my( $group_readings, $groups, $apsp ) = @_;
    my %contig;
    my $conflict = {};
    foreach my $g ( sort { scalar @$b <=> scalar @$a } @$groups ) {
        my @members = @$g;
        my $gst = wit_stringify( $g );
        map { $contig{$_} = $gst } @members; # The witnesses need themselves to be 
                                             # in their collection.
        next unless @members > 1;
        my $curr = pop @members;
        foreach my $m ( @members ) {
            foreach my $v ( $apsp->path_vertices( $curr, $m ) ) {
                $contig{$v} = $gst unless exists $contig{$v};
                next if $contig{$v} eq $gst;
                # print STDERR "Conflict at $v between group $gst and group " 
                #     . $contig{$v} . "\n";
                # Record what is conflicting.
                $conflict->{$group_readings->{$gst}} = $group_readings->{$contig{$v}};
            }
        }
    }
    return $conflict;
}

# Add the variant, subject to a.c. representation logic.
# This assumes that we will see the 'main' version before the a.c. version.
sub add_variant_wit {
    my( $arr, $wit ) = @_;
    my $acstr = $tradition->collation->ac_label;
    my $skip;
    if( $wit =~ /^(.*)\Q$acstr\E$/ ) {
        my $real = $1;
        $skip = grep { $_ =~ /^\Q$real\E$/ } @$arr;
    } 
    push( @$arr, $wit ) unless $skip;
}

# Return an answer if the variant is useful, i.e. if there are at least 2 variants
# with at least 2 witnesses each.
sub useful_variant {
    my( $readings ) = @_;
    my $total = keys %$readings;
    foreach my $var ( keys %$readings ) {
        $total-- if @{$readings->{$var}} == 1;
    }
    return( undef, undef ) if $total <= 1;
    my( $groups, $text );
    foreach my $var ( keys %$readings ) {
        push( @$groups, $readings->{$var} );
        push( @$text, $var );
    }
    return( $groups, $text );
}

# Take an array of witness groupings and produce a string like
# ['A','B'] / ['C','D','E'] / ['F']

sub wit_stringify {
    my $groups = shift;
    my @gst;
    # If we were passed an array of witnesses instead of an array of 
    # groupings, then "group" the witnesses first.
    unless( ref( $groups->[0] ) ) {
        my $mkgrp = [ $groups ];
        $groups = $mkgrp;
    }
    foreach my $g ( @$groups ) {
        push( @gst, '[' . join( ',', map { "'$_'" } @$g ) . ']' );
    }
    return join( ' / ', @gst );
}
    
1;